The DNA that makes up human chromosomes provides the instructions that direct the production of all proteins in the body. These proteins carry out the vital functions of life. Variations in the sequence of DNA encoding a protein produce variations or mutations in the proteins encoded, thus affecting the normal function of cells. Although environment often plays a significant role in disease, variations and/or mutations in the DNA of an individual are directly related to almost all human diseases, including cardiovascular, metabolic and infectious disease, cancer, and autoimmune disorders. Moreover, knowledge of genetics, particularly human genetics, has led to the realization that many diseases result from either complex interactions of several genes or their products. For example, Type I and II diabetes have been linked to multiple genes, each with its own pattern of mutations.
Additionally, knowledge of human genetics has led to a limited understanding of variations between individuals when it comes to drug response—the field of pharmocogenetics. Over half a century ago, adverse drug responses were correlated with amino acid variations in two drug-metabolizing enzymes, plasma cholinesterase and glucose-6-phosphate dehydrogenase. Since then, careful genetic analyses have linked sequence polymorphisms (variations) in over 35 drug metabolism enzymes, 25 drug targets and 5 drug transporters with compromised levels of drug efficacy or safety (Evans and Relling, Science 296:487–91 (1999)). In the clinic, such information is being used to prevent drug toxicity; for example, patients are screened routinely for genetic differences in the thiopurine methyltransferase gene that cause decreased metabolism of 6-mercaptopurine or azathiopurine. Yet only a small percentage of observed drug toxicities have been explained adequately by the set of pharmacogenetic markers validated to date. Even more common than toxicity issues may be cases where drugs demonstrated to be safe and/or efficacious for some individuals have been found to have either insufficient therapeutic efficacy or unanticipated side effects in other individuals.
Because any two humans are 99.9% similar in their genetic makeup, most of the sequence of the DNA of their genomes is identical. However, there are variations in DNA sequence between individuals. For example, there are deletions of many-base stretches of DNA, insertion of stretches of DNA, variations in the number of repetitive DNA elements in coding or non-coding regions, and changes in single nitrogenous base positions in the genome called “single nucleotide polymorphisms” (SNPs). Human DNA sequence variation accounts for a large fraction of observed differences between individuals, including susceptibility or resistance to disease and how an individual will respond to a particular therapeutic or treatment regimen.
Multifactorial traits, or complex traits, are influenced by multiple factors, such as genes, environmental factors, and their interactions. Often, more than one combination of genetic and/or environmental factors will result in the same multifactorial trait, and this complexity makes it difficult to determine who will develop such a trait. Further, the contribution of each factor is typically not identical to the contributions of every other factor. That is, for example, some factors may have a very strong contribution while others may have a very weak contribution. To complicate the biological basis of multifactorial traits even more, the contributions of a factor may be additive, synergistic, or completely independent from the contribution of any other factor. Some complex traits manifest common diseases, such as cardiovascular disease, diabetes, obesity, and high cholesterol. Other complex traits include such phenotypes as the way in which an individual responds to a drug or other medical treatment regimen.
In the recent past, research into the genetic basis for disease has resulted in the development of a few genetic tests for diseases. However, these genetic tests will not be useful for predicting a healthy person's probability of developing a common multifactorial disease. Many argue that genetic testing for common multifactorial traits (e.g. diseases) will not be useful in practice due to the incomplete penetrance and low individual contribution of each gene involved (Holtzman and Marteau, 2000; Vineis et al. 2001). However, these arguments are based in large part on the use of single loci to predict whether or not an individual will exhibit the trait (Beaudet 1999; Evans et al. 2001). What is needed is a reliable approach for determining an individual's risk of developing or exhibiting a multifactorial trait that is based on the individual's genotype at a plurality of loci, each of which are factors in the manifestation of the multifactorial trait.